Conventionally, various pattern recognition methods have been proposed. For example, as a technique for recognizing a pattern including a plurality of categories, a pattern recognition method which improves recognition accuracy using a probability of correct solutions of the recognition results of respective categories is known. As an example of such pattern recognition method, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, No. 1, pp. 68-83, January 1989 (non-patent reference 1) discloses a method which defines a value obtained by dividing a posterior probability by a prior probability as an evaluation value, and selects a candidate which maximizes the evaluation value as a next search target. Note that the posterior probability is written as P(c|x). The posterior probability P(c|x) is defined to mean a probability that a candidate c is a correct solution under the condition of an output x obtained by recognition processing. The prior probability is written as P(c). The prior probability P(c) is defined to mean a probability that a candidate c is a correct solution in a stage before recognition processing.
As an attempt to convert similarities of respective categories into posterior probabilities, that disclosed by Japanese Patent Registration No. 2739950 is known. With the technique disclosed by Japanese Patent Registration No. 2739950, when a similarity sj of a certain category Cj is given, a posterior probability P(Cj|sj) as the category Cj is to be calculated. However, it is difficult for the technique disclosed by Japanese Patent Registration No. 2739950 to improve the accuracy, since it considers only the similarity sj of one category, as described above.